Critical swim speed and fast-start response in the African cichlid<i>Pseudocrenilabrus multicolor victoriae</i>: convergent performance in divergent oxygen regimes
Bibliographic record
Abstract
Dissolved oxygen (DO) can be a strong predictor of intraspecific variation in morphology and physiology in fishes. In the African cichlid Pseudocrenilabrus multicolor victoriae Seegers, 1990, fish reared under low DO develop larger gills, deeper bodies, and larger, wider heads than full siblings reared under high DO, which could influence swim performance. In this study, we compared critical swim speed (Ucrit) and fast-start swimming in F1-generation fish from two field populations (one high and one low DO) of P. m. victoriae reared under high or low DO. There was no difference in Ucritbetween populations or rearing treatments. However, females exhibited a lower Ucritthan males. In fast-start trials, low-DO-reared fish reacted faster (lower response latency) and used double bends more often than high-DO-reared fish, but there was no difference in maximum velocity or acceleration. Low-DO-reared fish might compensate for morphological differences by using double bends to achieve similar performance as high-DO siblings. These results suggest that divergent morphotypes of P. m. victoriae are capable of achieving the same level of performance under their home DO condition and highlights the importance of developmental plasticity in facilitating adaptive response to alternative environments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".